Architecture of Computing Systems – ARCS 2014: 27th by Erik Maehle, Kay Römer, Wolfgang Karl, Eduardo Tovar PDF

By Erik Maehle, Kay Römer, Wolfgang Karl, Eduardo Tovar

ISBN-10: 3319048902

ISBN-13: 9783319048901

ISBN-10: 3319048910

ISBN-13: 9783319048918

This ebook constitutes the lawsuits of the twenty seventh overseas convention on structure of Computing structures, ARCS 2014, held in Lubeck, Germany, in February 2014. The 20 papers provided during this quantity have been conscientiously reviewed and chosen from forty four submissions. they're geared up in topical sections named: parallelization: functions and techniques self-organization and belief process layout method layout and sensor platforms and virtualization: I/O, reminiscence, cloud dependability: security, safety, and reliability elements.

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Extra info for Architecture of Computing Systems – ARCS 2014: 27th International Conference, Lübeck, Germany, February 25-28, 2014. Proceedings

Example text

In each stage parallel for templates are used to divide the workload into parallel tasks. The difference compared to Blackscholes is that a special parameter of the parallel for template, the grain size, is used to ensure a minimum size for each task. Similar with Blackscholes, Fig. 2 shows a low parallel/sequential ratio as well as a sub-linear speedup. Because Bodytrack has larger sequential regions throughout the execution, the average number of threads that are active during the execution is lower than for the other benchmarks.

Overall we recorded an increase with all “bad” metrics like the number of failed stealing attempts, the number of conflicts and backoffs. However, the sequential scanning for victims is “cheaper” in terms of executed instructions than the default method which can be seen in Fig. 4. Again, in terms of energy footprint Blackscholes, Bodytrack and Fluidanimate performed only marginally better or even worse than the default random selection. Streamcluster is the only benchmarked that showed improvements in all our test (see Fig.

All these provide a wide test base for our study. 1. which we customized in order to isolate and measure the overheads introduced by task spawning, task de-queuing and task stealing. We added special instructions called markers in the beginning and at the end of each function of interest to allow us to make measurements on the enclosed region of code. To ensure statistically stable results, we performed 10 simulations of each benchmark for every core count. We averaged the performance results before estimating the power requirements.

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Architecture of Computing Systems – ARCS 2014: 27th International Conference, Lübeck, Germany, February 25-28, 2014. Proceedings by Erik Maehle, Kay Römer, Wolfgang Karl, Eduardo Tovar


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